Ocean and Polar Research

Korea Institute of Ocean Science & Technology (한국해양과학기술원)
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Analysis of Price Forecasting and Goodness-of-Fit of the Metals Extracted from Deep Seabed Manganese Nodules

심해저 망간단괴에서 추출되는 금속가격 예측 및 적합도 분석

  • 권석재 (한국해양과학기술원 해양정책연구소) ;
  • 정선영 (한국해양과학기술원 해양정책연구소)
  • Received : 2014.10.26
  • Accepted : 2014.12.09
  • Published : 2014.12.30
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Abstract

The development of deep seabed manganese nodules has been carried out with the aim of commercial development in 2023. It is important to forecast the price of the four metals (copper, nickel, cobalt, and manganese) extracted from manganese nodules because price change is a criterion for investment decision. The main purpose of the study is to forecast the price of four metals using the ARIMA model and VAR model, and calculate the MAPE to compare a goodness-of-fit between the two models. The estimated results of the two models reveal statistical significance and are in keeping with economic theory. The results of MAPE for goodness-of-fit show that the VAR model is between 0.1 and 0.2, and the ARIMA model is between 0.4 and 0.6. That is, the VAR model is better than the ARIMA model in forecasting changes in the price of metals.

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References

  1. 문권순 (1997) 벡터자기회귀(VAR)모형의 이해. 통계분석연구 2(1):23-56(Moon K-S (1997) A Understanding of Vector Autoregressive Model. Journal of The Korean Official Statistics 2(1):23-56 (in Korean))
  2. 박완규, 홍성표 (2009) Gujarati 계량경제학(제5판). 지필 미디어(Park W-G, Hong S-P (2009) Gujarati Basic Econometrics 5/E. JIPHIL (in Korean))
  3. 이철용 (2010) 국제 유가 중.장기예측모형 개발-베이지안추론 이용 보고서(Lee C-Y (2010) Development of Long-term Oil Price Forecasting Model-Using Bayesian Inference. Korea Energy Economics Institute (in Korean))
  4. 정선경 (2006) VAR모형을 이용한 분기GDP 예측모형 연구 보고서(Jung S-K (2006) A Study on Quarterly GDP Forecasting Model Using the VAR Model. Statistical Research Institute (in Korean))
  5. 최병옥, 최익창 (2007) 시계열 분석방법을 이용한 과채류 월별가격 예측. 농촌경제 30(1):129-148(Choi B-O, Choi I-C (2007) Monthly price forecasting of fruit-type vegetables using time-series analysis. J Rural Development 30(1):129-148 (in Korean))
  6. 한국과학기술정책연구원 (2007) 심해저 광물자원(망간단괴) 개발 경제성 분석 평가 보고서(STEPI (2007) A Economic Analysis for the Development of Deep Seabed Mineral Resources (Manganese Nodules) (in Korean))
  7. 한국해양과학기술원 (2012) 심해저 광물자원 개발사업 보고서 III. 법제도분석(KIOST (2012) A Study on the Strategy for the Development of Deep Seabed Mineral Resources (III. Legal Regime Analysis) (in Korean))
  8. 한국해양과학기술원 (2013) 심해저 광물자원 개발사업 보고서 III. 법제도분석(KIOST (2013) A Study on the Strategy for the Development of Deep Seabed Mineral Resources (III. Legal Regime Analysis) (in Korean))
  9. 한국해양연구소 (1990) 심해저 광물자원 개발전략연구(II) 보고서(KORDI (1990) A Study on the Strategy for the Development of Deep Seabed Mineral Resources (II) (in Korean))
  10. 한국해양연구소 (1992) 심해저 광물자원 개발 연구 보고서(KORDI (1992) A Study on the Strategy for the Development of Deep Seabed Mineral Resources (in Korean))
  11. 한국해양연구원 (2002) 심해저 광물자원탐사 보고서(III. 심해저 자원개발 제도 분석)(KORDI (2002) A Study on the Strategy for the Development of Deep Seabed Mineral Resources (III. The Development of Deep Seabed Resources Regime Analysis) (in Korean))
  12. Bekiros SD, Diks CGH (2008) The relationship between Crude oil spot and future price: Cointegation, Linear and Nonlinear Causality. Energy Economics 30(5):2673-2685 https://doi.org/10.1016/j.eneco.2008.03.006
  13. Box GEP, Jenkins GM (1976) Time Series Analysis: Forecasting and control. revised edition, Holden-Day Inc. San Francisco.
  14. Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74(366):426-431
  15. Granger CWJ (1969) Investigating causal relationships by econometric models and cross-spectral method. Econometrica 37(3):424-438 https://doi.org/10.2307/1912791
  16. Gujarati D. (2002) Basic Econometrics, 4th edition, McGraw-Hill, New York
  17. Johansen S (1991) Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59(6):1551-1580 https://doi.org/10.2307/2938278
  18. Kaufmann RK, Ulman B (2009) Oil prices, speculation, and fundamentals, interpreting causal relations among spot and future prices. Energy Economics 31:550-558 https://doi.org/10.1016/j.eneco.2009.01.013
  19. Phillips PCB (1987) Testing for a Unit Root in Time Series Regression. Biometrika 75(2):335-346
  20. Phillips PCB (1987) Time series regression with a unit root. Econometrica 55:277-301 https://doi.org/10.2307/1913237
  21. Said SE, Dickey DA (1985) Hypothesis Testing in ARIMA (p, 1, q) Models. J Am Stat Asso 80:369-374 https://doi.org/10.1080/01621459.1985.10478125
  22. Sims CA (1980) Macroeconomics and Reality, Econometrica 48:1-48 https://doi.org/10.2307/1912017
  23. USGS http://www.usgs.gov/ Accessed 10 Oct 2014